Susceptibility to Photosynthesis Suppression From Extreme Storms Is Highly Site-Dependent

Extreme storms are becoming more intense and frequent under climate change. Although these extreme wet events are smaller in extent and duration than drought events, recent evidence suggests the global impact of both extremes is similar. However, the impact of individual extreme storms on photosynthesis—and therefore on vegetation and the carbon cycle—remains difficult to predict, as photosynthesis may be suppressed via waterlogging or increased by the alleviation of moisture stress. Here, we use random forest models to calculate daily photosynthesis anomalies attributable to extreme soil moisture using data from 54 FLUXNET sites across the globe. We hypothesize that photosynthesis' response to a given extreme event is primarily controlled by storm intensity, and to a lesser degree by site vegetation, climate, soil, and topography. However, we find instead that photosynthesis responses are better explained by site characteristics (soil texture, climate, topography, and vegetation density) than by storm intensity, such that the likelihood of waterlogging from a given storm is heavily site‐dependent. Although storms that induce waterlogging are roughly as common as those that induce stress alleviation overall, photosynthesis rarely declines at sites not prone to waterlogging. Instead, photosynthesis anomalies at these sites show a much weaker relationship with storm intensity. Increasingly intense storms are therefore unlikely to impact all locations equally. This highlights the potential to use site characteristics to enhance prediction of storm effects on ecosystems and the land carbon sink.

E.L.M. was funded by the NSF Graduate Research Fellowship and the Stanford “Diversifying Academia, Recruiting Excellence (DARE)” doctoral fellowship. A.G.K. and E.L.M. were also funded by the Alfred P. Sloan Foundation. D.F. was supported by the Stanford Institute for Human-Centered Artificial Intelligence (HAI) postdoctoral fellowship. C.A.F. was supported by the National Aeronautics and Space Administration under Grant No. 80NSSC21K1593 issued through the Future Investigators in NASA Earth and Space Science and Technology (FINESST) program. A.M.M. was funded through the Carnegie Institution for Science endowment.